SpreadPandas: data frame to spreadsheet mapping

What is it?

SpreadPandas is a Python package to get the projected dimensions of a pandas data frame if it were to be transposed to a spreadsheet.

By creating a SpreadsheetMap object, understand which cells of a spreadsheet the data frame would occupy, with detail for its header, index and body.

The goal is for this package to serve as a basis to perform more complex operations, like Excel customization or Google Sheet exporting, that require to establish a precise mapping between the data frame content and the target cells.

Quick Start

Installation

You can install EasyPred via pip

pip install spreadpandas

Alternatively, you can install EasyPred by cloning the project to your local directory

git clone https://github.com/FilippoPisello/SpreadPandas

And then run setup.py

python setup.py install

Usage

Take an example pandas data frame:

>>> import pandas as pd
>>> df = pd.DataFrame({"COL1" : [1, 2, 3], "COL2" : [4, 5, 6]})
>>> df
   COL1  COL2
0     1     4
1     2     5
2     3     6

Use SpreadMap to get its spreadsheet mapping. Suppose the index should not be brought over to the spreadsheet:

>>> from spreadpandas import SpreadMap
>>> spreadmap = SpreadMap(df, keep_index=False)
>>> spreadmap.header.cells
('A1', 'B1')
>>> spreadmap.body.cells
('A2', 'B2', 'A3', 'B3', 'A4', 'B4')
>>> spreadmap.index
None

If the index should be kept instead:

>>> spreadmap = SpreadMap(df, keep_index=True)
>>> spreadmap.header.cells
('B1', 'C1')
>>> spreadmap.body.cells
('B2', 'C2', 'B3', 'C3', 'B4', 'C4')
>>> spreadmap.index.cells
('A2', 'A3', 'A4')

The content can also be moved by skipping rows and/or columns:

>>> spreadmap = SpreadMap(df, keep_index=True, skip_rows=2, skip_columns=1)
>>> spreadmap.header.cells
('C3', 'D3')
>>> spreadmap.body.cells
('C4', 'D4', 'C5', 'D5', 'C6', 'D6')
>>> spreadmap.index.cells
('B4', 'B5', 'B6')

Dependencies

EasyPred depends only on pandas.

Documentation

For the moment, this is the only documentation available.

License

MIT